DocumentCode :
2571344
Title :
Viewpoint independent vehicle speed estimation from uncalibrated traffic surveillance cameras
Author :
Mao, Haili ; Ye, Chengxi ; Song, Mingli ; Bu, Jiajun ; Li, Na
Author_Institution :
Coll. of Comput. Sci., Zhejiang Univ., Hangzhou, China
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
4920
Lastpage :
4925
Abstract :
We present here a prototype of an algorithm for vehicle speed estimation. Different from previous approaches, our algorithm requires no road markers and fewer manual calibrations. Based on specific projection rules, we find a relation between the in-camera coordinate and the real world coordinate. A non-linear regression is employed to estimate the model parameters. This model enables us to estimate the real world position of the vehicles directly from a video sequence taken by a surveillance camera. The algorithm shows its ability to produce accurate estimations in our experiments.
Keywords :
image sequences; parameter estimation; road traffic; road vehicles; video cameras; model parameter estimation; nonlinear regression; uncalibrated traffic surveillance cameras; video sequence; viewpoint independent vehicle speed estimation; Calibration; Cameras; Land vehicles; Parameter estimation; Radar tracking; Road vehicles; Surveillance; Traffic control; Vehicle detection; Video sequences; Kalman filter; Vehicle speed estimate; camera calibration; projection model; surveillance camera; tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5346288
Filename :
5346288
Link To Document :
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